Methodology for distinguishing the cost of products in a multiple part number, multiple technology, fully or partially loaded semiconductor fabricator

ABSTRACT

A method of, computer system for, and computer program product for causally relating costs to products comprises, identifying resource costs for manufacturing the product, computing load factors for each of the resource costs, producing weighted resource costs based on the resource costs and the load factors, summing the weighted resource costs for the product, determining a volume of the product manufactured, and dividing the weighted resource costs by the volume to produce a weighted cost per product.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to methods for allocating costand more particularly to a causal methodology for costing productprocessing.

2. Description of the Related Art

The spiraling cost of semiconductor production has driven the industryto pursue greater economies of scale. This trend has forced a move fromsmaller, single partnumber fabricators to bigger, multiple partnumber,multiple technology fabricators. Costing is easy in a single partnumberfabricator and involves simply dividing total spending by the totalunits produced. Difficulties arise in costing wafer processing not as aresult of complex processing or advanced tooling requirements, butrather as a result of diverse and extensive product offerings. Multiplepartnumber, multiple technology fabricators must develop methodologiesfor costing different products. Traditional accounting systems trackcost by department, not by partnumber, so developing a methodology whichaccurately assigns cost by partnumber becomes a key concern.Conventional cost-of-ownership models provide detailed cost data ofequipment assets but not wafer processing costs. What is needed is acost model that goes beyond classical cost-of-ownership data to provideaccurate processing costs for such items as semiconductor wafers.

SUMMARY OF THE INVENTION

It is, therefore, an object of the present invention to provide astructure and method for a wafer processing cost model. The inventivecost-of-processing model provides wafer processing cost data from rawwafer through final passivation and parametric testing. This new modelgoes beyond conventional cost-of-ownership data and captures more thanjust equipment costs because process, product, and fabricator costs arealso captured. These costs are then causally spread to wafers viavarious methodologies. In order to do this, some historical costproblems had to be addressed, such as how to properly weight equipmentusage and account for dedicated equipment requirements, deal withmeasurement sampling, incorporate idle time and contingency, and accountfor different photolithographic field sizes. Output from the model wasfully validated against actual spending and tied to accounting data inorder to assure a full dollar capture.

More specifically, one embodiment of the invention comprises a methodof, computer system for, and computer program product for causallyrelating costs to products comprising, identifying resource costs formanufacturing the product, computing load factors for each of theresource costs, producing weighted resource costs based on the resourcecosts and the load factors, summing the weighted resource costs for theproduct, determining a volume of the product manufactured, and dividingthe weighted resource costs by the volume to produce a weighted cost perproduct.

The process of identifying resource costs comprises identifyingequipment costs, identifying partnumber costs, identifing technologycosts, and identifying factory costs. The process of computing loadfactors comprises determining a percentage of a time period the productis processed on an equipment element, the equipment element having theequipment costs, and the process of producing weighted resource costscomprises multiplying the equipment costs by the percentage. Similarly,the process of identifying equipment costs comprises assigning costs ofone or more of depreciation, spare parts, operator staffing, maintenancesupport, and vendor service contracts to the equipment element, androlling up costs of related peripheral equipment to the equipmentelement.

The process of computing load factors for the equipment costs comprisesallocating indirect equipment costs, including at least one of power,deionized water, bulk chemical usage, air filtration, air purification,hoods, transfer equipment, air showers, minienvironments, gas-isolationboxes and other peripheral equipment to the equipment element.

Similarly, the process of computing load factors for the partnumbercosts comprises allocating a portion of costs of one or more of yieldanalysis, systems setup, mask-set qualification, process tailoring, rawmaterials and engineering activities to the product based on an age ofthe product. Further, the process of computing load factors for thetechnology costs comprises allocating a portion of costs of one or moreof process qualification, routing creation, recipe creation, processwindow definition, design of process controls and yield planning to theproduct based on an age of the product. The process of computing loadfactors for the factory costs comprises allocating a portion of costs ofone or more of administrative services, data processing, garment rooms,break areas and systems support to the product.

The process of identifing resource costs includes determining optionalprocess costs, and the process of computing load factors includescomputing load factors for at least one optional process based on avolume of the products subjected to the optional process. Also, theprocess of determining a volume of the product manufactured comprisessubstituting a predetermined full capacity volume for the volume of theproduct manufactured.

The process of determining a volume of the product manufacturedcomprises subtracting an amount of rework and scrap from the volume ofthe product manufactured. Also, the process of comprising verifying theweighted cost per product.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, aspects and advantages will be betterunderstood from the following detailed description of preferredembodiments of the invention with reference to the drawings, in which:

FIGS. 1A-1C illustrate examples of tool entity components, shared entitycomponents and clustered tool entities;

FIG. 1D illustrates a numerical example of the invention applied todifferent tools and different tool groups;

FIGS. 2A-2B illustrate numerical examples of the invention applied todifferent operations;

FIG. 3 is a schematic diagram of different density wafers;

FIG. 4 is a numerical example of fill absorption cost and full capacitycosts according to the invention;

FIG. 5 is a schematic diagram of a computer systems used to implementthe invention;

FIG. 6 is a block diagram illustrating one embodiment of the inventivemethod; and

FIG. 7 is a block diagram showing an overview of the invention.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS OF THE INVENTION

The invention models wafer processing cost from raw wafer through finalpassivation and parametric testing. It also captures more than justequipment costs, focusing as well on the product, technology, andfabricator costs associated with producing multiple partnumber andmultiple technology devices. These costs are then causally assigned towafers using various methodologies.

To do this, a number of historical cost problems are addressed, such ashow to properly weight equipment usage and account for dedicatedequipment requirements, deal with measurement sampling, incorporate idletime and contingency, and account for different photolithographic fieldsizes. Output from the model is fully validated against actual spendingand tied to accounting data in order to assure a full dollar capture.

More specifically, with the invention, semiconductor manufacturing costsare broadly divided into four categories-equipment, partnumber,technology, and factory-related expenses. Each of these cost“components” contributes to the overall cost of the finished wafer.

The invention will be described with respect to semiconductor wafermanufacturing. However, the invention is not limited to semiconductorwafer manufacturing and is equally applicable to any form amanufacturing or costing process or model.

Semiconductor wafers are processed through highly specializedstate-of-the-art tools (e.g., “equipment”) with costs shared by eachwafer being processed. Cost is also accrued by wafers from“partnumber”—related activities such as yield analysis, systems setup,mask-set qualification, and process tailoring. In addition, each waferis manufactured using a specific processing “technology”. Engineeringactivities associated with introducing and supporting each technologyinclude process qualification, routing and recipe creation, processwindow definition, design of process controls, and yield planning.Finally, there are the factory overhead costs (e.g., “factory-relatedexpenses”) that are shared by all wafers being run in the fabricatorsuch as administrative services, data processing, garment rooms, breakareas, and systems support.

To properly assign cost to semiconductor wafers, each of the fourcomponents—equipment, partnumber, technology, and fabricatorexpenses—must be identified, weighted and assigned to the wafers. Thesecomponents are discussed in greater detail below.

Equipment Costs

Two requirements must be met to accurately weight and assign equipmentcosts to wafers. First, the equipment costs, themselves, must beaccurate. Second, there must be a methodology for assigning the cost ofthe equipment to the wafers.

To meet the first requirement, costs are matched to the equipment.Depreciation, spare parts, operator staffing, maintenance support, andvendor service contracts are matched precisely to specific pieces ofequipment.

When it is difficult to know which costs were incurred by which tools,the invention uses an allocation methodology for assigning costs totools. For example, unless power consumption is metered at each tool, itis difficult to know the power consumption for each individual tool.Otherwise, all that is known is the power consumption for the entirefactory. The invention includes a methodology which assigns the computedpower consumption to each tool.

Examples of such costs that are treated in this way are power, deionizedwater, bulk chemical usage, and air filtration and purification. Afterthe cost of individual tools is identified, the costs are thencollectively rolled up to the tool “entity” level. This means, forexample, that the cost of hoods, transfer equipment, air showers,minienviromnments, gas-isolation boxes, and other peripheral equipmentare summed with their “parent” equipment. Clustered tools are treated inthe same fashion.

In “rolling up” or adding together equipment costs, several factors areconsidered. In the case of peripheral equipment that does not producewafers (such as the hood 100 and gas cabinet 102 depicted in FIG. 1A)and which can clearly be identified as supporting a single tool 101, allcosts are summed.

At the very least this would entail summing the depreciation for eachpiece of equipment. If the peripheral equipment takes up floor space,(like the gas cabinet 102), it will also have an occupancy charge.Maintenance costs as well are summed (even hoods and gas cabinets may attimes require servicing) as well as all other spare parts or associatedcosts.

In the case of “shared” peripheral equipment (see FIG. 1B), the cost ofshared equipment (e.g., hood 110, gas cabinet 113) is divided equallybetween all main tools 111, 112 that are supported.

Clustered equipment is handled in a similar fashion, even thoughclustered equipment differs from peripheral equipment in several ways.Clustered equipment (see FIG. 1C) typically comprises at least two mainwafer-producing tools 121, 123 that are linked together. An example ofthis would be an apply tool linked to an expose tool. Both may haveperipheral equipment (e.g., hoods 120, 121) as well. Since they arelinked, they are treated as a single wafer-producing entity, with allcosts incurred by both being added together.

This collection of equipment-related costs alone is valuable. Indeed,costs can be derived from the conventional cost-of-ownership data isessential to understanding the cost of equipment assets. The inventivecost-of-processing model takes cost-of-ownership data one step furtherby causally relating the cost of the equipment to the wafers run on theequipment. This is accomplished using both raw process time, exposuretime (for chip based methodology) and wafer volume as weighting factors.

Referring now to FIG. 1D, a “load factor” is computed using both the rawprocess time and number of wafers of each operation being run on eachtool in the fabricator. Weighting is performed again at the operationallevel to identify the single cost of each operation. Once all costs havebeen assigned to operations with load factors, operational costs arethen added together to compute a total processing cost for each type ofwafer being manufactured.

More specifically, FIG. 1D illustrates two different tools, tool A andtool B. The costs, including depreciation, materials, staffing and otherfacilities overhead (e.g., lights, power, water) for each of the toolsis as shown in FIG. 1D. Specifically, tool A has a total daily cost of$2,650 and tool B has a daily cost of $5,450.

Three exemplary operations (operation x, operation y and operation z)are illustrated for each of the tools A and B. A cost per wafer for eachof the tools is calculated as follows. The number of minutes required toprocess a wafer is multiplied by the number of wafers processed in agiven day to determine the minutes and hours per day the tool willperform the different operations x, y and z. A load factor is formulatedaccording to the percentage of time each operation uses of the tool'stotal daily operation time. For example, operation x requires 200minutes of a total 800 minute operating day, which results in a loadfactor of 0.25 for operation x on tool A.

The load factor is multiplied by the daily cost of the tool to producean apportioned cost for each of the given operations on each of thetools. Therefore, operation x on tool A would have an apportioned costof 0.25 times $2,650 equaling $662.50. The apportioned cost is thendivided by the number of wafers processed in a given operation in agiven day to produce a tool-specific, operational cost per wafer.Therefore, in the example of tool A shown in FIG. 1D, the apportionedcost of operation x of $662.50 would be divided by 200 wafers, whichwould result in a cost for wafer of $3.31. A similar calculation isperformed for the remaining operations and on tool A all operations ontool B, as illustrated in FIG. 1D.

The average cost of different routes (e.g., route 1 and route 2) is thencalculated as shown at the bottom of FIG. 1D. The different routesillustrated in FIG. 1D utilize tool A and tool B differently to producedifferent loads. Because of the different daily cost of tools A and B,the different loading of tools A and B produces different average costsper wafer. For example, with respect to operation x in route 1, tool Ais used for 200 wafers and tool B is used for 50 wafers, which resultsin a 0.8 load on tool A and 0.2 load on tool B.

The various loads are multiplied by the above-calculated cost per waferto weight the cost per wafer for a given operation at a given tool. Forexample in operation x, the load of 0.8 is multiplied by the cost perwafer of $3.31 which results in an average cost per wafer of $2.65. Theweighted costs per wafer for each tool are then added to determine theroute-specific average cost per wafer of each operation.

This process is repeated for each operation within route 1, so that atotal average cost per wafer may be computed. Similar calculations aremade for route 2. Note that in this example, route 2 utilizes only themore expensive tool B and, thus, has a total average cost per waferwhich is higher than route 1.

Partnumber & Technology Costs

Partnumber costs are specific costs associated with individualpartnumbers. These include, for example, a raw wafer, aphotolithographic mask set, and engineering activities required tointroduce the partnumber to production, characterize parametricfeatures, and analyze yield. Once partnumber-related costs have beenassessed, they are assigned to wafers based on the age of the particularpartnumber (how long it has been running in the fabricator). With thismethodology, newer partnumbers are accorded a larger share ofengineering dollars and costed higher than older partnumbers. Forexample, if the total cost of engineering supporting existingpartnumbers is $500 and nine partnumbers are being produced, one ofwhich is new and eight of which are existing, and a weight of 2:1 couldbe selected for weighting new partnumbers to existing, then each of theexisting partnumbers would be assigned $50 engineering cost while thenew partnumber would be assigned $100.

Technology costs are handled in a similar fashion. These costs includethe engineering activities required to develop and qualify the processas a whole, establish processing controls, and conduct yield-learninganalysis. Once assessed, these costs are assigned to wafers based bothon the age of the technology and its volume in the line. Consequently,newer technologies, especially those being ramped up for production, areaccorded a larger share of the engineering cost. Similarly, if the totalcost of engineering supporting technologies is $1000 and seventechnologies are being produced, one of which is new and six of whichare existing, and a weight of 4:1 is chosen for weighting newtechnologies to existing, then each of the existing technologies wouldbe assigned $100 engineering cost while the new technology would beassigned $400.

Factory Costs

All costs not associated with equipment, partnumbers, or technologiesare considered to be factory overhead; that is, they are a necessarypart of running the factory as a whole and all wafers that run in thefactory must share in these costs. Examples of factory overhead arecosts associated with garment rooms and break areas, instrumentservices, information systems, administrative services, and dataprocessing.

Also part of factory overhead are those costs that, while causal, eitherlack enough data or are too data-intensive to warrant implementation ofcost-assigniment methodologies. Examples are costs associated withprocurement and installation services, mask-house operation, and productreliability activities.

Once collected, all factory overhead costs are shared equally by allwafers processed in the factory. This equal sharing is based roughly onthe amount of time each wafer spends in the fabricator. Wafers that havemore process steps (and require more of the overall fabricator'sresources to produce) are accordingly assigned a larger share ofoverhead cost.

Over time, and as better data sources become available, factory costsare preferably converted to equipment, product, or technology costs, andmore causally assigned to products.

Referring now to FIG. 6, the above-described embodiment of the inventivemethod is illustrated. More specifically, FIG. 6 illustrates, in item61, the summarizing of the history data (such as equipment cost,partnumber cost, technology cost, factory cost, etc.) for a desired timeperiod. In item 62 the cost data by tool is collected and rolled up tothe entity level, as discussed above with respect to FIGS. 1A-1C.

In item 63 the load factors for each piece of history data is computed,as shown for equipment costs in FIG. 1D. The load factors are used toapportion the history data costs between the various products beingmanufactured in the factory.

In item 64, the single cost per operation is computed by weightinghistory costs of each different operation performed using the loadfactors. For example, the load factors are used to weight the equipmentcosts to produce a single product cost per operation performed by thedifferent tools by volume through each tool, as discussed above withrespect to FIG. 1D.

In item 65 the weighted operation costs for each product are addedtogether. Each operation in the sequence is matched to its volume andoptional steps are weighted accordingly, as discussed in more detailbelow. In item 66 appropriate raw material, part number, technology andoverhead costs are added to routing and the full capacity costs arecomputed, as is also discussed below.

Referring now to FIG. 7, an overview of the inventive process isillustrated. More specifically, an input table 70 is illustrated thatreceives input from sources 71. The sources 71 input data such asdepreciation, chemical usage, spare parts usage, consumables usage,service contracts, staffing, BUDS coding, wafer data, tool plan targets,photo SPW, route data, raw process times and square footage for theprevious three months. As data from a new month is entered, data fromthe oldest of the month is purged.

The cost model equations 72, which are discussed above with respect toFIG. 6, are applied to the data in the input tables 70. The cost modelequations 72 output data to an output table 73. More specifically,output table 73 includes element cost, tool cost, operation cost, routecost, technology cost, error reports and validation reports. The outputtables 73 are preferably never purged so that the output tables 73continue to grow as new data is added each month.

The data is output from the output table 73 to various sources such asthe World Wide Web 74, a graphical user interface (GUI) 75 and to adatabase such as DB2 directly using, for example, structured querylanguage (SQL) 76.

Therefore, the invention identifies the resource costs that are involvedin the manufacturing of a product. The invention classifies theseresource costs as equipment costs, part number costs, technology costsand factory costs.

Then, the invention computes load factors for each of the resource costswhich logically match the cost to the product being manufactured. Theload factors are utilized to weight the resource costs appropriately toeach of the products manufactured. Once the weighted resource costs forspecific products are known, they are divided by the volume of theproduct manufactured to produce a weighted cost per product.

Measurement and Sampling

A second aspect of the invention is directed to accounting formeasurement and sampling operations in determining thecost-of-processing. Semiconductor products are manufactured byperforming a specific set of processing operations in a specific order.Most operations in the sequence are vital to the proper operation of thesemiconductor device. Other operations, such as measurement, inspection,and testing, do not add intrinsic value to the wafer but are a necessarypart of processing in order to assure that processing, as a whole, isperformed correctly. These “optional” operations are not alwaysperformed on each wafer; certain wafers are chosen to be representativeof the total wafer population and are the only ones measured (inspectedor tested).

Thus, a typical processing sequence will include a certain number ofprocessing steps, some of which may be optional. Simply summing the costof all operations in the sequence, without properly weighting theoperations where sampling occurs, would overstate the cost of theaverage wafer through the sequence because not every wafer is sampled.

More specifically, problems occur when historical data shows waferslogged through operations where sampling was performed, even though inreality only a fraction of the wafers were actually sampled. In thiscase, it is difficult to determine how many wafers were sampled or whatraw process time should be assigned to the lot.

The invention incorporates a methodology that properly weights eachoptional operation in the processing sequence depending upon howfrequently, on average, the optional operation is performed. Theinvention does this by identifying the cost of the optional operationsand weighting them by wafer volume flowing through each optional processover the total volume which flowed through the manufacturing processsequence.

There are two types of optional steps. The first type of optional stepis built into a sequence in order to give a choice regarding whichspecific processing a wafer will receive. These steps are built into theprocessing sequence to allow on-the-fly processing adjustments for avariety of reasons (i.e., device tailoring, yield analysis, parametricadjustment). The second type of optional step is a sampling step. Thistype of step is usually a measurement or inspection step, that will notbe performed on every wafer through the sequence but only on a sample ofwafers in order to draw statistical conclusions about the entirepopulation. Thus, the invention properly allocates the costs of optionalprocessing steps and results in more accurate costing of the entiresemiconductor processing sequence.

Examples of improper and proper cost allocation of optional processes isillustrated in FIGS. 2A and 2B. More specifically, in FIG. 2A fiveoperations (specifically, an apply step valued at $2.00, two exposesteps valued at $5.00 each, a develop step valued at $1.00, and ameasurement step valued at $1.00) added together for a total cost perwafer of $14.00. In reality, however, some of these steps are optional.Wafers being processed through this sequence will go through either oneor the other of the expose steps, and only one out of every 100 waferswill go through the measurement step. The optional nature of these stepsis apparent only upon viewing the wafer volumes through each of theprocessing steps (100 wafers through apply, 50 through each of theexpose steps, 100 through develop, and only 1 wafer through themeasurement step) shown in FIG. 2B. Using wafer volume, the cost of eachprocess step can be properly weighted, and a total cost per wafer of$8.01 is computed by summing the cost times volume of each process stepand dividing by the total number of wafers processed through thesequence (in this case, 100 wafers).

Therefore, the invention also properly allocates the resource costs foran optional processes by determining the optional process costs,computing load factors for the optional process, weighting the optionalprocesses using the load factors and dividing the weighted optionalprocess costs by the volume of the products subjected to the optionalprocess. The weighted per product cost is then added by to the other perproduct costs to produce a total weighted cost per product.

Exposure Field Size

Another aspect of the invention accounts for differences in exposurefield size when determining cost-of-processing and for allocating coststo individual wafers.

The majority of semiconductor operations are run on tools that processeswafers either individually or in batches. In either case, the basic unitof production is the wafer. Photolithographic operations differ fromother semiconductor operations because they are performed at the chiplevel rather than the wafer level. Consequently, the same weightingmethodologies used for wafer-based operations do not effectively workwith photolithographic operations. Problems arise because exposure fieldsize is variable and many different field sizes may be processed under asingle operation.

For instance, if it takes one minute to process a given wafer through agiven operation, it will take two minutes to process a wafer with twiceas many exposure fields through the same operation. In this case it isdifficult to know, looking at the historical data, which operationslasted one minute per wafer and which lasted two minutes. If historicaldata does not include information about the number of exposure fields(even the number of chips is not useful information since the chips maybe exposed in groups, or “matrixed”), the wafers cannot be properly“weighted” in the cost model.

For example, FIG. 3 illustrates a 48-chip wafer 31 and a 16-chip wafer30. If a throughput methodology for the tools on which these wafers areprocessed indicates that 1 minute is required to expose each chip on awafer, the 48-chip wafer will require 48 minutes to process and the16-chip wafer only 16 minutes, even though they are both receiving thesame processing (for example, exposure to 350 millijoules of ultravioletlight).

The invention builds photolithographic throughput methodologies into theabove cost-of-processing model to produce the chip based cost ofprocessing model. Throughput methodologies are based on machine type andmodel and are developed by modeling throughput of the machines usingelapsed time analysis, time and motion studies, and wafer and lottimings. The following shows the throughput equations used for exemplaryexposure tools. Each of the following equations computes raw-processtime in seconds per wafer given exposures per wafer.

Nikon 9-body RPT = 1.10 * #exp + 46.6 Nikon 10-body RPT = 0.90 * #exp +46.6 Nikon 11-body RPT = 0.70 * #exp + 42.1 Nikon 12-body RPT = 0.65 *#exp + 42.1 Nikon Wide Field RPT = 0.95 * #exp + 34.3 Micrascan II, IIP,and III RPT = 0.8374 * (#exp) ** 1.19863

These throughput equations enable raw process times to be computed giventhe photolithographic equipment type (manufacturer and model) and thenumber of exposures on the wafer. The number of exposures on each waferis derived from maximum and minimum field-count data taken directly fromwafer-build documentation.

Once raw process time has been computed for each wafer based on thenumber of exposures it requires, the model substitutes chip-level rawprocess time data for wafer-level data. This enables proper weightingand cost assignment of photolithographic operations. In other words, aswith the previous embodiments of the invention, the resource costs for awafer production are identified and the load factors are computed foreach of the resource costs.

In particular the load factor for the equipment costs are calculated bydetermining the number of exposure fields on a wafer, which allows theraw processing time for the wafer to be determined, using the abovemethodologies. The percentage that the raw processing time represents ofthe daily operating time of the tool is then used as the load factor.Again, as explained above, the load factor is multiplied by the dailytool cost to produce a weighted resource cost. The number of a giventype of wafer produced per day is then divided by the weighted cost toresult in an individual per wafer costs for the given tool operation.

Therefore, instead of determining cost per wafer, the costs are actuallydetermined per chip using the number of exposure fields. Therefore, theinvention accurately matches the equipment costs and other resourcecosts on a chip level instead of a wafer level.

Idle Time and Contingency

The standard view of the cost-of-processing model is based on theassumption that wafers run on equipment should fully “absorb” the costof that equipment. Consequently, wafers run on tools with a great dealof idle time (either planned or unplanned) will cost significantly morethan those run on tools with higher through puts, even if the wafersreceived the very same processing.

When unique processing drives special tooling in the factory that cannotbe used for other processing purposes, it seems appropriate to havethose wafers absorb the total cost of the equipment regardless of howmany or how few wafers are run. It may also be appropriate to assignwafers a higher cost when they run on newer, more expensive tools. Onthe other hand, it may not be appropriate to assign products withoutspecial requirements a higher cost just because the tools on which theywere processed did not run more wafers.

Costing methodologies that are historically based make use of actualprocessing data (comprised of operation and equipment details,) toassign costs to products. Based on this information, total spendingflows to products using various weighting methodologies. The problemwith this method is that if the fabricator is only partially loaded, thecost data produced by the model applies only to a partially loadedfabricator. As the fabricator fills and product volumes rise, the costof equipment assets should be applied to more wafers, with the resultbeing a lower cost per wafer.

Many historical costing methodologies based on actual data lack amethodology for predicting what will happen to cost as a partiallyloaded fabricator becomes fully loaded. Since business decisions basedon wafer cost and revenue are dependent on planned volume, the abilityto predict cost for any level of loading is critical to thedecision-making process. The invention incorporates a methodology forpredicting the cost of semiconductor products run in a fabricator at anylevel of target loading.

In one aspect of the invention, a “full-capacity” methodology usesequipment planning data to establish a predicted wafer volume based onplan targets. A ratio of planned wafer volume to actual wafer volume isused to recompile cost data in order to produce cost numbers based onplanned targets. As the name implies, full-capacity costs reflect thecost of wafers run on equipment, assuming that the equipment is runningto its targeted capacity.

For example, as shown in FIG. 4, the full absorption cost of a tool issimply the tool cost divided by the number of wafers processed on thattool in a given time, such as a daily time period. The full absorptionexample shown in FIG. 4 illustrates a tool with a cost of $2000 per daywhich runs 100 wafers per day resulting in a $20 per wafer cost.

To the contrary, the full capacity cost produces the cost per waferbased on the number of wafers that could be run if the tool was runningat target capacity. In the example shown in FIG. 4, the full capacitycost also has a tool having a $2000 cost per day which has a capacity of1152 wafers. The tool cost is divided by the number of wafer producedwhich results in a cost per wafer of $1.74.

Because the wafer history for a fabricator shows the actual number ofwafers produced each day by each machine (rather than the number ofwafers that could have been produced if each machine was running attarget capacity), a method is needed for computing full-capacity costwithout calculating individual load factors for each machine andoperation. The equation at the bottom of FIG. 4 shows that $1.74full-capacity operation cost can be derived from the full-absorptioncost by multiplying it by the ratio of actual production hours (100) totarget production hours (1152). This effectively ratios the entirefull-absorption cost up or down depending on whether each machineproduced more or less than its expected amount.

As such, the full-capacity cost represents a cost that would be achievedif the fabricator were running at target capacity. While it is not anactual cost (if the fabricator ran either more or less wafers thanexpected), it is an accurate cost. For the example in FIG. 4, while$1.74 would be the average cost per wafer if the tool had been runningto target capacity. Since only 100 wafers were run on the tool (whetherbecause the tool was down or inefficiently used), the actual cost perwafer is $20. While such underloading is undesirable in a fabricator, itis also a reality. The added expense of under utilized tools (averagedover the many operations it takes to produce a semiconductor wafer) willnot be as extreme as this example suggests. However, in the long runsuch inefficiencies must be taken into account if the fabricator is tobe profitable.

In reality, full-capacity can be defined in a number of ways including:targeted utilization, availability, or any other level of desired“fullness.” The capability to analyze several different targets at onceis built into the system to facilitate side-by-side cost analysis ofdifferent levels of fabricator loading. Using this methodology, costscan be produced with and without planned contingency, which providesvaluable insight into the cost of contingency itself.

Full-capacity costs are based on the assumption that each tool in thefabricator is running to its targeted capacity. However, actualfull-capacity will rarely be met in a fabricator with pinch-point toolsets (whether those pinch-points have been purposely designed in ornot). In a fabricator with these tool sets, full capacity costs will belower than total spending. Similarly, in a fabricator where tool targetsare set low and all equipment consistently runs “over capacity,”full-capacity costs will be higher than actual spending.

In summary, both full-absorption and full-capacity measure methodologiesprovide valuable cost data, while full-absorption costs provide a betterabsolute or actual cost, full-capacity costs provide a more accuratemeasure of relative cost and, therefore, are useful for comparative andplanning purposes.

Rework and Scrap

Rework data is usually very causal because a specific tool can beidentified as the cause of rework. Therefore, the invention subtractsrework data from the wafer history database so that only the good waferswhich are processed are reflected. The effect this has on cost is toraise it on tools that are causing rework.

For example, a tool costing $1000 a day to operate produces 1000 wafersa day at $1 per wafer. If, however, only 500 wafers are good (the other500 are the same wafers being reworked on the tool), then thecost-of-processing model computes the cost of the wafers as $2 perwafer. Subtracting reworked wafers from total wafers processed producesa cost for a good wafer. The drawback, however, is that the cost of allwafers run on the equipment will rise, rather than just the particularpartnumbers being reworked. This is not a problem where systemicequipment-related rework is concerned (i.e., all wafers are affected).

However, this method unfairly charges all wafers a higher equipment costif, indeed, rework is limited to only one particular partnumber orproduct. The potential for inaccuracy was conventionally consideredacceptable in light of the alternative, which is unassigned dollarsresulting from not accounting for reworked wafers.

Scrap, unlike rework, is often difficult to assign to a particularoperation or piece of equipment. Wafers scrapped “at” a certainoperation are more often, in reality, “discovered” at that operation(this is particularly true of measurement, inspection, and testoperations). Therefore, the cost-of-processing model does not assign thevalue of scrap wafers to individual tools. Since scrap wafers are notremoved from the wafer history, costs produced by the model areconsidered to be unyielded in terms of process loss due to scrap.

The cost model assembles a full product cost by summing individualoperation costs for a given production period. Individual lots or wafersare not tracked, and it is impossible to provide the cost of any onespecific lot that was processed. Operation costs remain stable whetherwafers are scrapped or not, another indication that costs are notyielded. Uplifts to account for process yield loss must be applied tocost-of-processing cost output where yielded data is required.

The removal or non-removal of scrap and rework wafer are inconsequentialto the overall workings of the model. They are mentioned here onlybecause it is considered important to know, one way or the other,whether the costs produced by a model are “per wafer” or “per goodwafer” and whether or not they are yielded. While this inventionproduces an unyielded cost per good wafer, it could easily be adjustedto provide a cost per wafer (good or bad) or a yielded answer. As such,a clarification of the numbers are produced by accounting for scrapitems.

Validation

To assure that all spending is captured and wafer costs tie to actualfinancial spending data, two forms of data checking are conducted eachtime the inventive model is run. First, dollars captured by the modelare totaled and checked against spending data as reported by the Financeorganization. The model also checks for sources of cost “leakage”(dollars captured by the model but not flowed to the product). Examplesof cost leakage are costs associated with tools that run no wafers, orcosts associated with operations that are not a part of waferfabrication.

These dollars are assessed and then “reflowed” in the model to insurethat all dollars are ultimately captured. As part of this analysis,individual cost elements (i.e., depreciation, salaries, chemicals) arechecked against actual spending to insure that they match. Not only areindividual cost elements checked, wafer counts are checked as well.

Performing this type of analysis every time the model is run insuresthat, over time, the model maintains a consistent level of accuracy andthat causality is also being maintained. Finally, cost times volume(C×Q) analyses of finished wafer costs are conducted to verify that alldollars are being captured and flowed to product wafers.

The classical cost-of-ownership part of the data is used by equipmentengineering to understand the cost of equipment over its lifetime, makeequipment purchasing decisions, and identify cost-efficient productionpractices and “problem” tools. Process engineers use the information tocompare operation costs in order to evaluate processing alternatives andfocus work on improving the most costly parts of processing.

Development engineers use the information to predict the cost of futureprocesses and product features. The information is used by management tomake decisions regarding which products are the most profitable tomanufacture. Finally, the information is used by Finance to helpestablish cost standards which are used to assign planned spendingdollars to products in accordance with accounting guidelines.

Indeed, it seems the potential uses for good cost data are limitless. Akey feature of the invention is that it not only establishes goodcausality, but also validates and ensures full dollar capture. Theinventive cost-of-processing model is a novel extension of classicalcost-of-ownership data. Together both sets of data can provide valuablecost data to virtually all organizations involved in any form ofproduction.

While the invention has been described with respect to an exemplarywafer processing environment, and has been described in the form of amanual process, it is equally applicable to all processing environmentsand all types of production lines. For example, the invention is equallyapplicable in a traditional mechanical factory setting or anon-traditional production process. Further, the invention includes acomputer system, a computer program and a storage medium containing thecomputer program for performing the above-described process.

A representative hardware environment for practicing the presentinvention is depicted in FIG. 5, which illustrates the typical hardwareconfiguration of an information handling/computer system in accordancewith the subject invention having at least one processor or centralprocessing unit (CPU) 10. The CPU 10 is interconnected via a system bus12 to a random access memory (RAM) 14, read-only memory (ROM) 16,input/output (I/O) adapter 18 (for connecting peripheral devices such asdisk units 20 to the bus 12), user interface adapter 22 (for connectinga keyboard 24, mouse 26, and/or other user interface device to the bus12), communication adapter 34 (for connecting an information handlingsystem to a data processing network), and display adapter 36 (forconnecting the bus 12 to a display device 38).

While the invention has been described in terms of preferredembodiments, those skilled in the art will recognize that the inventioncan be practiced with modification within the spirit and scope of theappended claims.

What is claimed is:
 1. A method of causally relating costs to a productcomprising: identifying historical resource costs for manufacturing saidproduct based, in part on partnumber costs; computing load factors foreach of said resource costs; producing weighted resource costs based onsaid resource costs and said load factors; summing said weightedresource costs for said product; determining a volume of said productmanufactured; and dividing said weighted resource costs by said volumeto produce a weighted cost per product.
 2. The method in claim 1,wherein: said identifying resource costs includes determining optionalprocess costs; and said computing load factors includes computing loadfactors for at least one optional process based on a volume of saidproducts subjected to said optional process.
 3. The method in claim 1,wherein said determining a volume of said product manufactured comprisessubstituting a predetermined full capacity volume for said volume ofsaid product manufactured.
 4. The method in claim 1, wherein saiddetermining a volume of said product manufactured comprises subtractingan amount of rework and scrap from said volume of said productmanufactured.
 5. The method as an claim 1, further comprising verifyingsaid weighted cost per product.
 6. The method in claim 1, wherein saididentifying resource costs comprises: identifying equipment costs;identifying said partnumber costs; identifying technology costs; andidentifying factory costs.
 7. The method in claim 6, wherein saidcomputing load factors for said equipment costs comprises allocatingindirect equipment costs, including at least one of power, deionizedwater, bulk chemical usage, air filtration, air purification, hoods,transfer equipment, air showers, mini environments, gas-isolation boxesand other peripheral equipment to said equipment element.
 8. The methodin claim 6, wherein said computing load factors for said partnumbercosts comprises allocating a portion of costs of one or more of yieldanalysis, systems setup, mask-set qualification, process tailoring, rawmaterials and engineering activities to said product based on an age ofsaid product.
 9. The method in claim 6, wherein said computing loadfactors for said technology costs comprises allocating a portion ofcosts of one or more of process qualification, routing creation, recipecreation, process window definition, design of process controls andyield planning to said product based on an age of said product.
 10. Themethod in claim 6, wherein said computing load factors for said factorycosts comprises allocating a portion of costs of one or more ofadministrative services, data processing, garment rooms, break areas andsystems support to said product.
 11. The method in claim 6, wherein:said computing load factors comprises determining a percentage of a timeperiod said product is processed on an equipment element, said equipmentelement having said equipment costs; and said producing weightedresource costs comprises multiplying said equipment costs by saidpercentage.
 12. The method in claim 11, wherein said identifyingequipment costs comprises: assigning costs of one or more ofdepreciation, spare parts, operator staffing, maintenance support, andvendor service contracts to said equipment element; and rolling up costsof related peripheral equipment to said equipment element.
 13. Acomputer system for causally relating costs to a product comprising: aunit for identifying historical resource costs for manufacturing saidproduct based, in part, on partnumber costs; a unit for computing loadfactors for each of said resource costs; a unit for producing weightedresource costs based on said resource costs and said load factors; aunit for summing said weighted resource costs for said product; a unitfor determining a volume of said product manufactured; and a unit fordividing said weighted resource costs by said volume to produce aweighted cost per product.
 14. The computer system in claim 13, wherein:said unit for identifying resource costs includes a unit for determiningoptional process costs; and said unit for computing load factorsincludes a unit for computing load factors for at least one optionalprocess based on a volume of said products subjected to said optionalprocess.
 15. The computer system in claim 13, wherein said unit fordetermining a volume of said product manufactured comprises a unit forsubstituting a predetermined full capacity volume for said volume ofsaid product manufactured.
 16. The computer system in claim 13, whereinsaid unit for determining a volume of said product manufacturedcomprises a unit for subtracting an amount of rework and scrap from saidvolume of said product manufactured.
 17. The computer system as an claim13, further comprising a unit for verifying said weighted cost perproduct.
 18. The computer system in claim 13, wherein said unit foridentifying resource costs comprises: a unit for identifying equipmentcosts; a unit for identifying said partnumber costs; a unit foridentifying technology costs; and a unit for identifying factory costs.19. The computer system in claim 18, wherein said unit for computingload factors for said equipment costs comprises a unit for allocatingindirect equipment costs, including at least one of power, deionizedwater, bulk chemical usage, air filtration, air purification, hoods,transfer equipment, air showers, mini environments, gas-isolation boxesand other peripheral equipment to said equipment element.
 20. Thecomputer system in claim 18, wherein said unit for computing loadfactors for said partnumber costs comprises a unit for allocating aportion of costs of one or more of yield analysis, systems setup,mask-set qualification, process tailoring, raw materials and engineeringactivities to said product based on an age of said product.
 21. Thecomputer system in claim 18, wherein said unit for computing loadfactors for said technology costs comprises a unit for allocating aportion of costs of one or more of process qualification, routingcreation, recipe creation, process window definition, design of processcontrols and yield planning to said product based on an age of saidproduct.
 22. The computer system in claim 18, wherein said unit forcomputing load factors for said factory costs comprises a unit forallocating a portion of costs of one or more of administrative services,data processing, garment rooms, break areas and systems support to saidproduct.
 23. The computer system in claim 18, wherein: said unit forcomputing load factors comprises a unit for determining a percentage ofa time period said product is processed on an equipment element, saidequipment element having said equipment costs; and said unit forproducing weighted resource costs comprises a unit for multiplying saidequipment costs by said percentage.
 24. The computer system in claim 23,wherein said unit for identifying equipment costs comprises: a unit forassigning costs of one or more of depreciation, spare parts, operatorstaffing, maintenance support, and vendor service contracts to saidequipment element; and a unit for rolling up costs of related peripheralequipment to said equipment element.
 25. A computer program productcomprising a program storage device readable by a computer systemtangibly embodying a program of instructions executed by said computersystem to perform in a process for causally relating costs to a product,said process comprising: identifying resource costs for manufacturingsaid product based, in part, on partnumber costs; computing load factorsfor each of said resource costs; producing weighted resource costs basedon said resource costs and said load factors; summing said weightedresource costs for said product; determining a volume of said productmanufactured; and dividing said weighted resource costs by said volumeto produce a weighted cost per product.
 26. The computer program productin claim 25, wherein: said identifying resource costs includesdetermining optional process costs; and said computing load factorsincludes computing load factors for at least one optional process basedon a volume of said products subjected to said optional process.
 27. Thecomputer program product in claim 25, wherein said determining a volumeof said product manufactured comprises substituting a predetermined fullcapacity volume for said volume of said product manufactured.
 28. Thecomputer program product in claim 25, wherein said determining a volumeof said product manufactured comprises subtracting an amount of reworkand scrap from said volume of said product manufactured.
 29. Thecomputer program product as an claim 25, further comprising verifyingsaid weighted cost per product.
 30. The computer program product inclaim 25, wherein said identifying resource costs comprises: identifyingequipment costs; identifying said partnumber costs; identifyingtechnology costs; and identifying factory costs.
 31. The computerprogram product in claim 30, wherein said computing load factors forsaid equipment costs comprises allocating indirect equipment costs,including at least one of power, deionized water, bulk chemical usage,air filtration, air purification, hoods, transfer equipment, airshowers, mini environments, gas-isolation boxes and other peripheralequipment to said equipment element.
 32. The computer program product inclaim 30, wherein said computing load factors for said partnumber costscomprises allocating a portion of costs of one or more of yieldanalysis, systems setup, mask-set qualification, process tailoring, rawmaterials and engineering activities to said product based on an age ofsaid product.
 33. The computer program product in claim 30, wherein saidcomputing load factors for said technology costs comprises allocating aportion of costs of one or more of process qualification, routingcreation, recipe creation, process window definition, design of processcontrols and yield planning to said product based on an age of saidproduct.
 34. The computer program product in claim 30, wherein saidcomputing load factors for said factory costs comprises allocating aportion of costs of one or more of administrative services, dataprocessing, garment rooms, break areas and systems support to saidproduct.
 35. The computer program product in claim 30, wherein: saidcomputing load factors comprises determining a percentage of a timeperiod said product is processed on an equipment element, said equipmentelement having said equipment costs; and said producing weightedresource costs comprises multiplying said equipment costs by saidpercentage.
 36. The computer program product in claim 35, wherein saididentifying equipment costs comprises: assigning costs of one or more ofdepreciation, spare parts, operator staffing, maintenance support, andvendor service contracts to said equipment element; and rolling up costsof related peripheral equipment to said equipment element.